語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Distributed Decision Algorithms for ...
~
ProQuest Information and Learning Co.
Distributed Decision Algorithms for Fair Resource Allocations in Collaborative Networks.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Distributed Decision Algorithms for Fair Resource Allocations in Collaborative Networks./
作者:
Yilmaz, Ibrahim.
面頁冊數:
1 online resource (102 pages)
附註:
Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
標題:
Industrial engineering. -
電子資源:
click for full text (PQDT)
ISBN:
9780355858648
Distributed Decision Algorithms for Fair Resource Allocations in Collaborative Networks.
Yilmaz, Ibrahim.
Distributed Decision Algorithms for Fair Resource Allocations in Collaborative Networks.
- 1 online resource (102 pages)
Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
Thesis (Ph.D.)--State University of New York at Binghamton, 2018.
Includes bibliographical references
This research addresses distributed decisions for to enhance fairness and total profit among collaborative networked enterprises (CNEs). The arbitrary nature of demand and capacity patterns in manufacturing/service enterprises require to form a CNE with other enterprises to overcome such uncertainties. In any CNE, the collaboration process often leads to a dilemma: the need to choose between fairness and total profit. The aim of this research is to investigate a new sharing protocol (SP) to control CNEs and to propose an algorithm that attempts to increase optimal weights of fairness while maintaining total profit. Most CNE research studies have been designed under a centralized SP. However, centralized SPs appear to be unfeasible or inadequate because of enterprises' operating environments and local objectives; therefore, each CNE requires a distributed decision-making mechanism. Furthermore, market globalization and competition necessitate rapid responses to market changes and give rise to two major concerns about CNEs: 1) how can collaborations be rendered re-configurable to dynamically capture and adapt to market patterns; and 2) how can the resources of all CNEs be utilized fairly among enterprises, ensuring mutual benefits? Therefore, Dynamic-Distributed Sharing Protocol (D2SP ), which is inspired by the principles of Collaborative Control Theory and the Contract Net Protocol, is proposed to address these concerns. Under the assumptions used in this research, experimental results and analyses indicate that D2SP reduces the number of messages and inventory cost of shared amounts by up to 30%, and 9%, respectively and total profit and fairness index are increased by up to 15% and 10%, respectively. The proposed algorithm in which Jain's fairness index and the generalized alpha-fair concept are utilized, is tested with conceptual heterogeneous and homogeneous CNs (HeCNs and HoCNs, respectively) based on the enterprise capacity. Experimental results indicate that fairness increases up to 28% in HeCN and 32% in HoCN while maintaining the current total profit of a CN. The gap between two CNEs, which are the most benefited and least benefited enterprises in terms of total profit, lost sale cost, and inventory cost, can reduce up to 57%, 54%, and 78%, respectively. Therefore, the proposed algorithm can minimize the deviation between most and least beneficial CNEs in terms of total profit, lost sale cost, and inventory cost.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9780355858648Subjects--Topical Terms:
679492
Industrial engineering.
Index Terms--Genre/Form:
554714
Electronic books.
Distributed Decision Algorithms for Fair Resource Allocations in Collaborative Networks.
LDR
:03679ntm a2200337K 4500
001
915369
005
20180727125214.5
006
m o u
007
cr mn||||a|a||
008
190606s2018 xx obm 000 0 eng d
020
$a
9780355858648
035
$a
(MiAaPQ)AAI10791525
035
$a
(MiAaPQ)binghamton:12676
035
$a
AAI10791525
040
$a
MiAaPQ
$b
eng
$c
MiAaPQ
100
1
$a
Yilmaz, Ibrahim.
$3
1188698
245
1 0
$a
Distributed Decision Algorithms for Fair Resource Allocations in Collaborative Networks.
264
0
$c
2018
300
$a
1 online resource (102 pages)
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
500
$a
Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
500
$a
Adviser: Sang W. Yoon.
502
$a
Thesis (Ph.D.)--State University of New York at Binghamton, 2018.
504
$a
Includes bibliographical references
520
$a
This research addresses distributed decisions for to enhance fairness and total profit among collaborative networked enterprises (CNEs). The arbitrary nature of demand and capacity patterns in manufacturing/service enterprises require to form a CNE with other enterprises to overcome such uncertainties. In any CNE, the collaboration process often leads to a dilemma: the need to choose between fairness and total profit. The aim of this research is to investigate a new sharing protocol (SP) to control CNEs and to propose an algorithm that attempts to increase optimal weights of fairness while maintaining total profit. Most CNE research studies have been designed under a centralized SP. However, centralized SPs appear to be unfeasible or inadequate because of enterprises' operating environments and local objectives; therefore, each CNE requires a distributed decision-making mechanism. Furthermore, market globalization and competition necessitate rapid responses to market changes and give rise to two major concerns about CNEs: 1) how can collaborations be rendered re-configurable to dynamically capture and adapt to market patterns; and 2) how can the resources of all CNEs be utilized fairly among enterprises, ensuring mutual benefits? Therefore, Dynamic-Distributed Sharing Protocol (D2SP ), which is inspired by the principles of Collaborative Control Theory and the Contract Net Protocol, is proposed to address these concerns. Under the assumptions used in this research, experimental results and analyses indicate that D2SP reduces the number of messages and inventory cost of shared amounts by up to 30%, and 9%, respectively and total profit and fairness index are increased by up to 15% and 10%, respectively. The proposed algorithm in which Jain's fairness index and the generalized alpha-fair concept are utilized, is tested with conceptual heterogeneous and homogeneous CNs (HeCNs and HoCNs, respectively) based on the enterprise capacity. Experimental results indicate that fairness increases up to 28% in HeCN and 32% in HoCN while maintaining the current total profit of a CN. The gap between two CNEs, which are the most benefited and least benefited enterprises in terms of total profit, lost sale cost, and inventory cost, can reduce up to 57%, 54%, and 78%, respectively. Therefore, the proposed algorithm can minimize the deviation between most and least beneficial CNEs in terms of total profit, lost sale cost, and inventory cost.
533
$a
Electronic reproduction.
$b
Ann Arbor, Mich. :
$c
ProQuest,
$d
2018
538
$a
Mode of access: World Wide Web
650
4
$a
Industrial engineering.
$3
679492
650
4
$a
Systems science.
$3
1148479
650
4
$a
Operations research.
$3
573517
655
7
$a
Electronic books.
$2
local
$3
554714
690
$a
0546
690
$a
0790
690
$a
0796
710
2
$a
ProQuest Information and Learning Co.
$3
1178819
710
2
$a
State University of New York at Binghamton.
$b
Systems Science Industrial Engineering.
$3
1182293
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10791525
$z
click for full text (PQDT)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入